Traditional physical and occupational therapy for stroke patients, such as the Bobath approach and the Motor Relearning Program, typically involve exercises that attempt to overcome motor deficits and improve motor patterns with the help of therapists. More recently, promising results have been demonstrated in Constraint-induced Movement Therapy, which forces the use of the affected limb by restraining the unaffected limb. Although the above rehabilitation methods are well-established in practice, they are labor intensive and expensive. Furthermore, manually assisted movement training lacks repeatability and objective measures of patient performance and therapy progress.
With the advent of robotic technology and new insights in the neuroscience of human motor adaptation, there is a paradigm shift to robot-assisted motor rehabilitation. Rehabilitation programs that incorporate robotic and information technology can ameliorate the increasing burden on manpower by automating parts of the process that are repetitive and time-consuming. Additionally, robots are able to provide pervasive and accurate monitoring of the progress of patients. However, most of the current robotic rehabilitation approaches are centered on physical therapy, and devote minimal emphasis to cognitive factors that play a role in determining rehabilitation progress and outcome.
Current approaches of robot-assisted motor rehabilitation tailor adaptive therapy only to changes in behavioral measures of motor skills and may not capture all the facets of an optimal therapy. The behavioral measures of motor performance may not provide any indication of the degree of cognitive effort or the level of psychological stress in the patient. Furthermore, the perception of task difficulty and self-evaluation of progress can vary across patients in view of individual factors that include attitude, self-motivation, and personality.
A need therefore exists to provide a system and method for motor learning that seeks to address at least one of the abovementioned problems.